零膨胀泊松模型的变量选择及应用
Variable Selection and Application of Zero Inflated Poisson Model
DOI: 10.12677/SA.2023.122034, PDF,   
作者: 马元凯：云南师范大学数学学院，云南 昆明
关键词: 零膨胀泊松模型；变量选择；EM算法；Zero Inflated Poisson Model； Variable Selection； EM Algorithm
摘要: 零膨胀泊松模型是研究零过多的计数数据的方法。在实际应用中，为避免遗漏，常选择过多变量进行分析，因此需要对模型进行变量选择，本文在零膨胀泊松模型的基础上构造模型进行变量选择，本文通过研究影响德国卫生保健需求的因素，对比岭回归、Lasso、自适应Lasso和加权弹性网方法的效果。
Abstract: The zero inflated Poisson model is a method to study zero and excessive counting data. In practical application, in order to avoid omission, many variables are often selected for statistical analysis, so it is necessary to select variables for the model. This paper compares the effects of ridge regression, Lasso, adaptive Lasso and weighted elastic network by studying the factors affecting the demand for health care in Germany.
文章引用：马元凯. 零膨胀泊松模型的变量选择及应用[J]. 统计学与应用, 2023, 12(2): 327-331. https://doi.org/10.12677/SA.2023.122034

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